Machine Learning Engineering InternFull-time

Role Overview

Join our ML engineering team to explore cutting-edge machine learning technologies, develop scalable AI solutions, and contribute to real-world applications. This collaborative learning opportunity focuses on end-to-end ML pipeline development, model deployment, and production system optimization.

Key Responsibilities

• Design, develop, and optimize machine learning models using Python, TensorFlow, PyTorch, and scikit-learn frameworks
• Build and maintain robust ML pipelines from data preprocessing through model deployment and monitoring
• Conduct data analysis, feature engineering, and statistical validation to ensure high-quality model performance
• Implement model evaluation frameworks and A/B testing infrastructure for continuous improvement
• Collaborate with cross-functional teams including data scientists, software engineers, and product managers
• Deploy ML models to production environments using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)
• Participate in code reviews, technical discussions, and contribute to research publications when applicable

Required Qualifications

Must-Haves

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (final year students or recent graduates)
• Strong programming proficiency in Python with experience in NumPy, Pandas, and machine learning libraries
• Solid understanding of machine learning algorithms including supervised/unsupervised learning, neural networks, and deep learning
• Knowledge of data structures, algorithms, and software engineering best practices
• Experience with version control systems (Git) and collaborative development workflows

Nice-to-Haves

• Hands-on experience with deep learning frameworks like TensorFlow, PyTorch, or Keras
• Familiarity with MLOps practices, model deployment, and production monitoring systems
• Understanding of computer vision, natural language processing, or reinforcement learning applications
• Experience with cloud-based ML services and containerization technologies
• Previous internship experience or significant open-source contributions in ML/AI projects

Learning Outcomes and Development

• Gain hands-on experience with end-to-end ML system development from research to production deployment
• Master industry-standard ML engineering tools, frameworks, and methodologies through mentorship from senior engineers
• Develop expertise in scalable ML infrastructure, model optimization, and performance monitoring techniques
• Build comprehensive understanding of real-world ML challenges including data quality, bias evaluation, and system reliability
• Access to cutting-edge research projects with potential for academic publications and conference presentations
• Enhanced collaboration skills through cross-functional team projects and regular technical presentations

Duration: 6 months
Hours: 09:00 AM to 06:00 PM (Monday to Friday)
Location: Ganesh Glory 11, Jagatpur, Ahmedabad, 382470 (Offline Internship)